We propose ideas for the development of TEL systems which allow for an automatic, dynamic and self-adapting recommendation of curricula from a wide set of available content for an individual user and with regard to a specific purpose. We argue that recommender systems in the prevalent occurrence cannot be used directly in TEL systems, but must be extended by process-related techniques for continuous optimization and adaptation of the generated curriculum. © 2013 Springer-Verlag.
CITATION STYLE
Bab, S., & Kranich, L. (2013). On self-adapting recommendations of curricula for an individual learning experience. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8095 LNCS, pp. 589–590). https://doi.org/10.1007/978-3-642-40814-4_65
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